Automatic Question Generation using Relative Pronouns and Adverbs

Payal Khullar, Konigari Rachna, Mukul Hase, Manish Shrivastava


Abstract
This paper presents a system that automatically generates multiple, natural language questions using relative pronouns and relative adverbs from complex English sentences. Our system is syntax-based, runs on dependency parse information of a single-sentence input, and achieves high accuracy in terms of syntactic correctness, semantic adequacy, fluency and uniqueness. One of the key advantages of our system, in comparison with other rule-based approaches, is that we nearly eliminate the chances of getting a wrong wh-word in the generated question, by fetching the requisite wh-word from the input sentence itself. Depending upon the input, we generate both factoid and descriptive type questions. To the best of our information, the exploitation of wh-pronouns and wh-adverbs to generate questions is novel in the Automatic Question Generation task.
Anthology ID:
P18-3022
Volume:
Proceedings of ACL 2018, Student Research Workshop
Month:
July
Year:
2018
Address:
Melbourne, Australia
Editors:
Vered Shwartz, Jeniya Tabassum, Rob Voigt, Wanxiang Che, Marie-Catherine de Marneffe, Malvina Nissim
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
153–158
Language:
URL:
https://aclanthology.org/P18-3022
DOI:
10.18653/v1/P18-3022
Bibkey:
Cite (ACL):
Payal Khullar, Konigari Rachna, Mukul Hase, and Manish Shrivastava. 2018. Automatic Question Generation using Relative Pronouns and Adverbs. In Proceedings of ACL 2018, Student Research Workshop, pages 153–158, Melbourne, Australia. Association for Computational Linguistics.
Cite (Informal):
Automatic Question Generation using Relative Pronouns and Adverbs (Khullar et al., ACL 2018)
Copy Citation:
PDF:
https://aclanthology.org/P18-3022.pdf